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Learning Plan Coach (AI) - Study Plan + Milestones

Under maintenance

Try for free

Create a personalized learning plan from any goal: milestones and daily tasks based on your time budget, duration, and constraints.

Pricing

Pay per usage

Rating

0.0

(0)

Developer

Anass

Actor stats

Bookmarked

Total users

Monthly active users

17 days ago

Last modified

.actor/actor.json

{
    "actorSpecification": 1,
    "name": "learning-plan-coach",
    "title": "Learning Plan Coach (AI) - Study Plan + Milestones",
    "description": "Create a personalized learning plan from any goal: milestones and daily tasks based on your time budget, duration, and constraints.",
    "version": "0.1",
    "dockerfile": "../Dockerfile",
    "input": "./input_schema.json",
    "output": "./output_schema.json",
    "storages": {
        "dataset": "./dataset_schema.json"
    }
}

.actor/dataset_schema.json

{
    "actorSpecification": 1,
    "title": "Learning Plan",
    "views": {
        "overview": {
            "title": "Tasks",
            "transformation": {
                "fields": [
                    "week",
                    "day",
                    "task",
                    "deliverable"
                ]
            },
            "display": {
                "component": "table",
                "properties": {
                    "week": { "label": "Week", "format": "number" },
                    "day": { "label": "Day", "format": "text" },
                    "task": { "label": "Task", "format": "text" },
                    "deliverable": { "label": "Deliverable", "format": "text" }
                }
            }
        }
    }
}

.actor/input_schema.json

{
  "title": "Learning Plan Coach (AI)",
  "type": "object",
  "schemaVersion": 1,
  "properties": {
    "goal": {
      "title": "Goal",
      "type": "string",
      "description": "Describe what you want to learn or achieve.",
      "editor": "textfield"
    },
    "currentLevel": {
      "title": "Current Level",
      "type": "string",
      "default": "Beginner",
      "description": "Your current level in the topic.",
      "editor": "select",
      "enum": ["Beginner", "Intermediate", "Advanced"]
    },
    "timePerDayMinutes": {
      "title": "Time Per Day (minutes)",
      "type": "integer",
      "default": 30,
      "description": "How much time you can spend per day.",
      "editor": "number",
      "minimum": 10,
      "maximum": 240
    },
    "durationWeeks": {
      "title": "Duration (weeks)",
      "type": "integer",
      "default": 6,
      "description": "How many weeks the plan should cover.",
      "editor": "number",
      "minimum": 1,
      "maximum": 52
    },
    "constraints": {
      "title": "Constraints",
      "type": "string",
      "default": "",
      "description": "Optional constraints (schedule limits, tools, preferences).",
      "editor": "textarea"
    }
  },
  "required": ["goal"]
}

.actor/output_schema.json

{
    "actorOutputSchemaVersion": 1,
    "title": "Learning Plan Output",
    "type": "object",
    "properties": {
        "results": {
            "type": "string",
            "title": "Plan Tasks",
            "template": "{{links.apiDefaultDatasetUrl}}/items"
        }
    }
}

assets/banner.svg

1<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="360" viewBox="0 0 1200 360">
2  <defs>
3    <linearGradient id="g" x1="0" y1="0" x2="1" y2="1">
4      <stop offset="0" stop-color="#0b1220"/>
5      <stop offset="1" stop-color="#22c55e"/>
6    </linearGradient>
7  </defs>
8  <rect width="1200" height="360" fill="url(#g)"/>
9  <text x="60" y="145" fill="#ffffff" font-size="56" font-family="Arial, Helvetica, sans-serif">Learning Plan Coach</text>
10  <text x="60" y="215" fill="#dcfce7" font-size="28" font-family="Arial, Helvetica, sans-serif">Goal → milestones • Weekly plan • Daily tasks</text>
11  <text x="60" y="285" fill="#bbf7d0" font-size="22" font-family="Arial, Helvetica, sans-serif">Apify Actor</text>
12</svg>

assets/flow.svg

1<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="360" viewBox="0 0 1200 360">
2  <rect width="1200" height="360" fill="#ffffff"/>
3  <rect x="60" y="80" width="430" height="200" rx="18" fill="#f3f4f6" stroke="#e5e7eb"/>
4  <rect x="710" y="80" width="430" height="200" rx="18" fill="#f0fdf4" stroke="#dcfce7"/>
5  <path d="M540 180 H660" stroke="#111827" stroke-width="6"/>
6  <path d="M660 180 l-18 -12 v24 z" fill="#111827"/>
7  <text x="90" y="125" fill="#111827" font-size="26" font-family="Arial, Helvetica, sans-serif">Input</text>
8  <text x="90" y="165" fill="#374151" font-size="20" font-family="Arial, Helvetica, sans-serif">• goal + currentLevel</text>
9  <text x="90" y="195" fill="#374151" font-size="20" font-family="Arial, Helvetica, sans-serif">• minutes/day + weeks</text>
10  <text x="90" y="225" fill="#374151" font-size="20" font-family="Arial, Helvetica, sans-serif">• constraints (optional)</text>
11  <text x="740" y="125" fill="#111827" font-size="26" font-family="Arial, Helvetica, sans-serif">Output</text>
12  <text x="740" y="165" fill="#166534" font-size="20" font-family="Arial, Helvetica, sans-serif">• Daily tasks dataset</text>
13  <text x="740" y="195" fill="#166534" font-size="20" font-family="Arial, Helvetica, sans-serif">• Deliverables per day</text>
14  <text x="740" y="225" fill="#166534" font-size="20" font-family="Arial, Helvetica, sans-serif">• Milestones implied by tasks</text>
15</svg>

src/pycache/main.cpython-310.pyc

Download

src/main.py

1import json
2import logging
3from typing import Any, Optional, List
4
5import requests
6from apify import Actor
7from requests.adapters import HTTPAdapter
8from urllib3.util.retry import Retry
9
10WORKER_URL = "https://gemini-proxy-worker.anass-seb3.workers.dev"
11
12# Order matters — most likely to work first
13MODEL_CANDIDATES: List[str] = [
14    "gemini-3-pro-preview",
15    "gemini-1.5-flash-8b",
16    "gemini-1.5-pro",
17    "gemini-1.0-pro",
18]
19
20REQUEST_TIMEOUT_SEC = 100
21MAX_OUTPUT_TOKENS = 8192
22
23
24def get_session() -> requests.Session:
25    s = requests.Session()
26    retry = Retry(
27        total=3,
28        backoff_factor=1.2,
29        status_forcelist=[429, 500, 502, 503, 504],
30        allowed_methods=["POST"],
31    )
32    adapter = HTTPAdapter(max_retries=retry)
33    s.mount("https://", adapter)
34    s.mount("http://", adapter)
35    return s
36
37
38session = get_session()
39
40
41def extract_json_content(raw: str) -> Optional[str]:
42    raw = raw.strip()
43
44    # Fast path — already clean JSON
45    try:
46        json.loads(raw)
47        return raw
48    except:
49        pass
50
51    # Common: ```json ... ```
52    if "```json" in raw:
53        start = raw.find("```json") + 7
54        end = raw.find("```", start)
55        if end > start:
56            return raw[start:end].strip()
57
58    # Fallback — find last complete object
59    start_idx = raw.rfind("{")
60    end_idx = raw.rfind("}") + 1
61    if start_idx >= 0 and end_idx > start_idx:
62        candidate = raw[start_idx:end_idx]
63        try:
64            json.loads(candidate)
65            return candidate
66        except:
67            pass
68
69    return None
70
71
72def call_gemini(prompt: str) -> Optional[dict]:
73    for model in MODEL_CANDIDATES:
74        Actor.log.info(f"Trying model: {model}")
75
76        url = f"{WORKER_URL}/v1beta/models/{model}:generateContent"
77        payload = {
78            "contents": [{"parts": [{"text": prompt}]}],
79            "generationConfig": {
80                "responseMimeType": "application/json",
81                "temperature": 0.2,
82                "maxOutputTokens": MAX_OUTPUT_TOKENS,
83            },
84        }
85
86        try:
87            resp = session.post(url, json=payload, timeout=REQUEST_TIMEOUT_SEC)
88        except Exception as e:
89            Actor.log.warning(f"Request error ({model}): {e}")
90            continue
91
92        if resp.status_code != 200:
93            Actor.log.warning(f"{model} → HTTP {resp.status_code}")
94            continue
95
96        try:
97            data = resp.json()
98            text = (
99                data.get("candidates", [{}])[0]
100                .get("content", {})
101                .get("parts", [{}])[0]
102                .get("text", "")
103            )
104        except Exception:
105            Actor.log.warning(f"Cannot extract text from {model}")
106            continue
107
108        if not text.strip():
109            continue
110
111        # Log first ~500 chars for debugging
112        preview = text[:450].replace("\n", " ").strip()
113        Actor.log.info(f"Raw output ({model}): {preview}...")
114
115        json_str = extract_json_content(text)
116        if not json_str:
117            continue
118
119        try:
120            parsed = json.loads(json_str)
121            if isinstance(parsed, dict):
122                return parsed
123        except Exception as e:
124            Actor.log.warning(f"JSON parse failed ({model}): {e}")
125
126    Actor.log.error("All model attempts failed")
127    return None
128
129
130async def main() -> None:
131    async with Actor:
132        inp = await Actor.get_input() or {}
133
134        goal = str(inp.get("goal") or "").strip()
135        level = str(inp.get("currentLevel") or "Beginner").strip()
136        minutes = int(inp.get("timePerDayMinutes") or 30)
137        weeks = int(inp.get("durationWeeks") or 6)
138        constraints = str(inp.get("constraints") or "").strip()
139
140        if not goal:
141            Actor.log.error("Goal is required")
142            await Actor.fail()
143            return
144
145        schema_example = {
146            "milestones": [{"week": 1, "milestone": "string"}],
147            "tasks": [
148                {
149                    "week": 1,
150                    "day": "Monday",
151                    "task": "string – clear & actionable",
152                    "deliverable": "string or null",
153                }
154            ],
155        }
156
157        prompt = f"""You are an experienced learning coach and curriculum designer.
158
159Create a realistic, progressive learning plan.
160
161Rules:
162- Return ONLY valid JSON — no explanations, no markdown
163- Use keys "milestones" and "tasks"
164- "milestones" → array of important checkpoints (one per few weeks)
165- "tasks" → detailed daily tasks
166- Days: Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday
167- Keep tasks realistic for {minutes} min/day
168- Adapt difficulty to "{level}" level
169- Respect constraints
170
171JSON example structure:
172{json.dumps(schema_example, indent=2)}
173
174INPUT:
175Goal: {goal}
176Current level: {level}
177Daily time: {minutes} minutes
178Total duration: {weeks} weeks
179Additional constraints / preferences:
180{constraints if constraints else "None"}
181
182Generate the plan now.
183""".strip()
184
185        result = call_gemini(prompt)
186
187        if not result or not isinstance(result, dict):
188            Actor.log.error("Model did not return valid structured output")
189            await Actor.fail()
190            return
191
192        # We mainly care about tasks
193        tasks = result.get("tasks", [])
194        if not isinstance(tasks, list):
195            Actor.log.error("'tasks' is not a list")
196            await Actor.fail()
197            return
198
199        pushed = 0
200
201        for item in tasks:
202            if not isinstance(item, dict):
203                continue
204
205            row = {
206                "week": int(item.get("week") or 0),
207                "day": str(item.get("day", "")).strip(),
208                "task": str(item.get("task", "")).strip(),
209                "deliverable": str(item.get("deliverable", "")).strip() or None,
210            }
211
212            if row["week"] < 1 or not row["task"]:
213                continue
214
215            await Actor.push_data(row)
216            pushed += 1
217
218        if pushed == 0:
219            Actor.log.warning("No valid tasks could be extracted")
220            await Actor.fail()
221            return
222
223        Actor.log.info(f"Successfully pushed {pushed} learning tasks")
224
225
226if __name__ == "__main__":
227    import asyncio
228    asyncio.run(main())

Dockerfile

FROM apify/actor-python:3.11

COPY requirements.txt ./
RUN pip install -r requirements.txt

COPY src ./src
CMD ["python3", "-m", "src.main"]

requirements.txt

1apify
2requests

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